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MLB Batting Splits 2026

Performance splits by handedness, home/away, and situational categories.

Batting splits break down a hitter's performance across different game situations. Platoon splits (vs LHP/RHP) are the most predictive for DFS and prop betting. Minimum 10 at-bats displayed.
Randal Grichuk headshot
Houston Astros
.533 OPS
AVG .200
OBP .200
SLG .333
HR 0
AB 15
H 3
RBI 2
Thomas Saggese headshot
Pittsburgh Pirates
.533 OPS
AVG .200
OBP .333
SLG .200
HR 0
AB 15
H 3
RBI 0
Eugenio Suarez headshot
Baltimore Orioles
.533 OPS
AVG .200
OBP .333
SLG .200
HR 0
AB 10
H 2
RBI 2
Cal Raleigh headshot
Baltimore Orioles
.533 OPS
AVG .200
OBP .333
SLG .200
HR 0
AB 10
H 2
RBI 2
Harry Ford headshot
Atlanta Braves
.533 OPS
AVG .200
OBP .333
SLG .200
HR 0
AB 10
H 2
RBI 0
Cody Bellinger headshot
Seattle Mariners
.533 OPS
AVG .200
OBP .333
SLG .200
HR 0
AB 10
H 2
RBI 0
Victor Scott II headshot
Pittsburgh Pirates
.533 OPS
AVG .111
OBP .200
SLG .333
HR 1
AB 18
H 2
RBI 1
Cody Bellinger headshot
Boston Red Sox
.532 OPS
AVG .200
OBP .265
SLG .267
HR 1
AB 45
H 9
RBI 3
Kaelen Culpepper headshot
Detroit Tigers
.532 OPS
AVG .208
OBP .240
SLG .292
HR 0
AB 24
H 5
RBI 3
Daylen Lile headshot
Milwaukee Brewers
.532 OPS
AVG .208
OBP .240
SLG .292
HR 0
AB 24
H 5
RBI 0
Justin Crawford headshot
New York Mets
.532 OPS
AVG .212
OBP .229
SLG .303
HR 0
AB 33
H 7
RBI 6
Mickey Gasper headshot
Tampa Bay Rays
.532 OPS
AVG .208
OBP .240
SLG .292
HR 0
AB 24
H 5
RBI 1
Josh Naylor headshot
Los Angeles Angels
.531 OPS
AVG .212
OBP .281
SLG .250
HR 0
AB 52
H 11
RBI 6
Michael Massey headshot
St. Louis Cardinals
.530 OPS
AVG .250
OBP .280
SLG .250
HR 0
AB 24
H 6
RBI 3
Drew Cavanaugh headshot
San Diego Padres
.530 OPS
AVG .091
OBP .167
SLG .364
HR 1
AB 11
H 1
RBI 2
Hector Rodriguez headshot
Milwaukee Brewers
.530 OPS
AVG .250
OBP .280
SLG .250
HR 0
AB 24
H 6
RBI 1
Luke Raley headshot
Baltimore Orioles
.530 OPS
AVG .091
OBP .167
SLG .364
HR 1
AB 11
H 1
RBI 2
Gunnar Henderson headshot
Seattle Mariners
.530 OPS
AVG .120
OBP .290
SLG .240
HR 1
AB 25
H 3
RBI 2
Spencer Steer headshot
Los Angeles Angels
.530 OPS
AVG .091
OBP .167
SLG .364
HR 1
AB 11
H 1
RBI 1
JJ Wetherholt headshot
Los Angeles Angels
.530 OPS
AVG .091
OBP .167
SLG .364
HR 1
AB 11
H 1
RBI 2
Casey Schmitt headshot
Kansas City Royals
.530 OPS
AVG .091
OBP .167
SLG .364
HR 1
AB 11
H 1
RBI 1
Heliot Ramos headshot
Kansas City Royals
.530 OPS
AVG .091
OBP .167
SLG .364
HR 1
AB 11
H 1
RBI 2
Jose Altuve headshot
Los Angeles Angels
.530 OPS
AVG .191
OBP .296
SLG .234
HR 0
AB 47
H 9
RBI 2
Michael Massey headshot
Chicago White Sox
.530 OPS
AVG .212
OBP .257
SLG .273
HR 0
AB 33
H 7
RBI 1
Junior Caminero headshot
Chicago Cubs
.530 OPS
AVG .091
OBP .167
SLG .364
HR 1
AB 11
H 1
RBI 1

Understanding Opponent Splits

Opponent splits reveal how a hitter performs against each MLB team. These splits capture the combined effect of a team's pitching staff, defensive alignment, and park factors. Some hitters consistently dominate certain teams due to favorable pitching matchups.

Team-Specific Matchups

Some hitters own certain teams. This often reflects favorable matchups against that team's pitching staff — handedness advantages, pitch-type weaknesses, or familiarity from division play. Division rivals face each other 13+ times per season, creating larger sample sizes.

Stacking by Opponent

For DFS, opponent splits help identify entire lineups to stack. If multiple hitters on a team have strong splits against today's opponent, that's a high-correlation stack. Combine with the opposing starter's recent form for maximum edge.

Sample Size Caution

Opponent splits against non-division teams can be small (3-4 games per season). Weight division matchups more heavily since they have 13+ games of data. A .400 AVG in 10 at-bats against a team is interesting but not predictive on its own.

Data Source & Methodology

Batting splits sourced from MLB Stats API. Stats reflect current season data and update daily as games are played.

Frequently Asked Questions

How reliable are opponent batting splits?

Division opponent splits are the most reliable since hitters face those teams 13+ times per season. Interleague and non-division splits have smaller sample sizes (3-7 games) and should be weighted less heavily. Always check the at-bat count before drawing conclusions.

How do I use opponent splits for DFS stacks?

Find teams where multiple hitters have strong splits against today's opponent. Stack 3-4 hitters from that team in your DFS lineup for high correlation. This works especially well when the opposing starter is also weak against that lineup's handedness profile.

Why do some hitters crush certain teams?

It usually comes down to pitching staff matchups. A hitter might face favorable pitch types, have platoon advantages against most of a team's rotation, or thrive at that team's home park. Division familiarity also plays a role — hitters see the same pitchers repeatedly.
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